/**
* Find transfer candidates for profile routing. TODO replace with an on-street search using the
* existing profile router functions.
*/
public Map<StopCluster, Double> findNearbyStopClusters(StopCluster sc, double radius) {
Map<StopCluster, Double> ret = Maps.newHashMap();
Envelope env = new Envelope(new Coordinate(sc.lon, sc.lat));
env.expandBy(
SphericalDistanceLibrary.metersToLonDegrees(radius, sc.lat),
SphericalDistanceLibrary.metersToDegrees(radius));
for (StopCluster cluster : stopClusterSpatialIndex.query(env)) {
// TODO this should account for area-like nature of clusters. Use size of bounding boxes.
double distance = distlib.distance(sc.lat, sc.lon, cluster.lat, cluster.lon);
if (distance < radius) ret.put(cluster, distance);
}
return ret;
}
@Override
public List<GraphPath> getPaths(RoutingRequest options) {
final Graph graph = graphService.getGraph(options.getRouterId());
if (options.rctx == null) {
options.setRoutingContext(graph);
options.rctx.pathParsers =
new PathParser[] {new BasicPathParser(), new NoThruTrafficPathParser()};
}
if (!options.getModes().isTransit()) {
return sptService.getShortestPathTree(options).getPaths();
}
// also fall back to A* for short trips
double distance =
distanceLibrary.distance(
options.rctx.origin.getCoordinate(), options.rctx.target.getCoordinate());
if (distance < shortPathCutoff) {
log.debug("Falling back to A* for very short path");
return shortPathService.getPaths(options);
}
RaptorDataService service = graph.getService(RaptorDataService.class);
if (service == null) {
log.warn("No raptor data. Rebuild with RaptorDataBuilder");
return Collections.emptyList();
}
RaptorData data = service.getData();
// we multiply the initial walk distance to account for epsilon dominance.
double initialWalk = options.getMaxWalkDistance() * WALK_EPSILON;
options.setMaxWalkDistance(initialWalk);
// do not even bother with obviously impossible walks
double minWalk =
options.rctx.origin.getDistanceToNearestTransitStop()
+ options.rctx.target.getDistanceToNearestTransitStop();
if (options.getMaxWalkDistance() < minWalk) {
options.setMaxWalkDistance(minWalk);
}
RoutingRequest walkOptions = options.clone();
walkOptions.rctx.pathParsers = new PathParser[0];
TraverseModeSet modes = options.getModes().clone();
modes.setTransit(false);
walkOptions.setModes(modes);
RaptorSearch search = new RaptorSearch(data, options);
if (data.maxTransitRegions != null) {
Calendar tripDate = Calendar.getInstance(graph.getTimeZone());
tripDate.setTime(new Date(1000L * options.dateTime));
Calendar maxTransitStart = Calendar.getInstance(graph.getTimeZone());
maxTransitStart.set(Calendar.YEAR, data.maxTransitRegions.startYear);
maxTransitStart.set(Calendar.MONTH, data.maxTransitRegions.startMonth);
maxTransitStart.set(Calendar.DAY_OF_MONTH, data.maxTransitRegions.startDay);
int day = 0;
while (tripDate.after(maxTransitStart)) {
day++;
tripDate.add(Calendar.DAY_OF_MONTH, -1);
}
if (day > data.maxTransitRegions.maxTransit.length || options.isWheelchairAccessible()) {
day = -1;
}
search.maxTimeDayIndex = day;
}
int rushAheadRound = preliminaryRaptorSearch(data, options, walkOptions, search);
long searchBeginTime = System.currentTimeMillis();
double expectedWorstTime =
1.5
* distanceLibrary.distance(
options.rctx.origin.getCoordinate(), options.rctx.target.getCoordinate())
/ options.getWalkSpeed();
int foundSoFar = 0;
double firstWalkDistance = 0;
List<RaptorState> targetStates = new ArrayList<RaptorState>();
do {
int bestElapsedTime = Integer.MAX_VALUE;
RETRY:
do {
for (int round = 0; round < options.getMaxTransfers() + 2; ++round) {
if (!round(data, options, walkOptions, search, round)) break;
long elapsed = System.currentTimeMillis() - searchBeginTime;
if (elapsed > multiPathTimeout * 1000 && multiPathTimeout > 0 && targetStates.size() > 0)
break RETRY;
ArrayList<RaptorState> toRemove = new ArrayList<RaptorState>();
for (RaptorState state : search.getTargetStates()) {
if (state.nBoardings == 0 && options.getMaxWalkDistance() > initialWalk) {
toRemove.add(state);
}
}
if (search.getTargetStates().size() > 0) {
if (firstWalkDistance == 0) {
firstWalkDistance = options.getMaxWalkDistance();
}
for (RaptorState state : toRemove) {
search.removeTargetState(state.walkPath);
}
}
if (targetStates.size() >= options.getNumItineraries() && round >= rushAheadRound) {
int oldBest = bestElapsedTime;
for (RaptorState state : search.getTargetStates()) {
final int elapsedTime = (int) Math.abs(state.arrivalTime - options.dateTime);
if (elapsedTime < bestElapsedTime) {
bestElapsedTime = elapsedTime;
}
}
int improvement = oldBest - bestElapsedTime;
if (improvement < 600 && bestElapsedTime < expectedWorstTime) break RETRY;
}
}
if (foundSoFar < search.getTargetStates().size()) {
foundSoFar = search.getTargetStates().size();
} else if (foundSoFar > 0) {
// we didn't find anything new in this round, and we already have
// some paths, so bail out
break;
}
options = options.clone();
walkOptions = walkOptions.clone();
if (search.getTargetStates().size() > 0 && bestElapsedTime < expectedWorstTime) {
// we have found some paths so we no longer want to expand the max walk distance
break RETRY;
} else {
options.setMaxWalkDistance(options.getMaxWalkDistance() * 2);
walkOptions.setMaxWalkDistance(options.getMaxWalkDistance());
options.setWalkReluctance(options.getWalkReluctance() * 2);
walkOptions.setWalkReluctance(options.getWalkReluctance());
}
search.reset(options);
} while (options.getMaxWalkDistance() < initialWalk * MAX_WALK_MULTIPLE
&& initialWalk < Double.MAX_VALUE);
options = options.clone();
walkOptions = walkOptions.clone();
for (RaptorState state : search.getTargetStates()) {
for (AgencyAndId trip : state.getTrips()) {
options.bannedTrips.add(trip);
}
}
if (search.getTargetStates().size() == 0) break; // no paths found; searching more won't help
options.setMaxWalkDistance(firstWalkDistance);
walkOptions.setMaxWalkDistance(firstWalkDistance);
targetStates.addAll(search.getTargetStates());
search = new RaptorSearch(data, options);
} while (targetStates.size() < options.getNumItineraries());
collectRoutesUsed(data, options, targetStates);
if (targetStates.isEmpty()) {
log.info("RAPTOR found no paths");
}
Collections.sort(targetStates);
if (targetStates.size() > options.getNumItineraries())
targetStates = targetStates.subList(0, options.getNumItineraries());
List<GraphPath> paths = new ArrayList<GraphPath>();
for (RaptorState targetState : targetStates) {
// reconstruct path
ArrayList<RaptorState> states = new ArrayList<RaptorState>();
RaptorState cur = targetState;
while (cur != null) {
states.add(cur);
cur = cur.getParent();
}
// states is in reverse order of time
State state = getState(targetState.getRequest(), data, states);
paths.add(new GraphPath(state, true));
}
return paths;
}
@Override
public List<GraphPath> getPaths(RoutingRequest options) {
if (options.rctx == null) {
options.setRoutingContext(graphService.getGraph(options.getRouterId()));
// move into setRoutingContext ?
options.rctx.pathParsers =
new PathParser[] {new BasicPathParser(), new NoThruTrafficPathParser()};
}
RemainingWeightHeuristic heuristic;
if (options.getModes().isTransit()) {
LOG.debug("Transit itinerary requested.");
// always use the bidirectional heuristic because the others are not precise enough
heuristic = new BidirectionalRemainingWeightHeuristic(options.rctx.graph);
} else {
LOG.debug("Non-transit itinerary requested.");
heuristic = new DefaultRemainingWeightHeuristic();
}
// the states that will eventually be turned into paths and returned
List<State> returnStates = new LinkedList<State>();
BinHeap<State> pq = new BinHeap<State>();
// List<State> boundingStates = new ArrayList<State>();
Vertex originVertex = options.rctx.origin;
Vertex targetVertex = options.rctx.target;
// increase maxWalk repeatedly in case hard limiting is in use
WALK:
for (double maxWalk = options.getMaxWalkDistance(); returnStates.isEmpty(); maxWalk *= 2) {
if (maxWalk != Double.MAX_VALUE && maxWalk > MAX_WALK) {
break;
}
LOG.debug("try search with max walk {}", maxWalk);
// increase maxWalk if settings make trip impossible
if (maxWalk
< Math.min(
distanceLibrary.distance(originVertex.getCoordinate(), targetVertex.getCoordinate()),
originVertex.getDistanceToNearestTransitStop()
+ targetVertex.getDistanceToNearestTransitStop())) continue WALK;
options.setMaxWalkDistance(maxWalk);
// cap search / heuristic weight
final double AVG_TRANSIT_SPEED = 25; // m/sec
double cutoff =
(distanceLibrary.distance(originVertex.getCoordinate(), targetVertex.getCoordinate())
* 1.5)
/ AVG_TRANSIT_SPEED; // wait time is irrelevant in the heuristic
cutoff += options.getMaxWalkDistance() * options.walkReluctance;
options.maxWeight = cutoff;
State origin = new State(options);
// (used to) initialize heuristic outside loop so table can be reused
heuristic.computeInitialWeight(origin, targetVertex);
options.maxWeight = cutoff + 30 * 60 * options.waitReluctance;
// reinitialize states for each retry
HashMap<Vertex, List<State>> states = new HashMap<Vertex, List<State>>();
pq.reset();
pq.insert(origin, 0);
long startTime = System.currentTimeMillis();
long endTime = startTime + (int) (_timeouts[0] * 1000);
LOG.debug("starttime {} endtime {}", startTime, endTime);
QUEUE:
while (!pq.empty()) {
if (System.currentTimeMillis() > endTime) {
LOG.debug("timeout at {} msec", System.currentTimeMillis() - startTime);
if (returnStates.isEmpty()) break WALK; // disable walk distance increases
else {
storeMemory();
break WALK;
}
}
// if (pq.peek_min_key() > options.maxWeight) {
// LOG.debug("max weight {} exceeded", options.maxWeight);
// break QUEUE;
// }
State su = pq.extract_min();
// for (State bs : boundingStates) {
// if (eDominates(bs, su)) {
// continue QUEUE;
// }
// }
Vertex u = su.getVertex();
if (traverseVisitor != null) {
traverseVisitor.visitVertex(su);
}
if (u.equals(targetVertex)) {
// boundingStates.add(su);
returnStates.add(su);
if (!options.getModes().isTransit()) break QUEUE;
// options should contain max itineraries
if (returnStates.size() >= _maxPaths) break QUEUE;
if (returnStates.size() < _timeouts.length) {
endTime = startTime + (int) (_timeouts[returnStates.size()] * 1000);
LOG.debug(
"{} path, set timeout to {}",
returnStates.size(),
_timeouts[returnStates.size()] * 1000);
}
continue QUEUE;
}
for (Edge e : options.isArriveBy() ? u.getIncoming() : u.getOutgoing()) {
STATE:
for (State new_sv = e.traverse(su); new_sv != null; new_sv = new_sv.getNextResult()) {
if (traverseVisitor != null) {
traverseVisitor.visitEdge(e, new_sv);
}
double h = heuristic.computeForwardWeight(new_sv, targetVertex);
if (h == Double.MAX_VALUE) continue;
// for (State bs : boundingStates) {
// if (eDominates(bs, new_sv)) {
// continue STATE;
// }
// }
Vertex v = new_sv.getVertex();
List<State> old_states = states.get(v);
if (old_states == null) {
old_states = new LinkedList<State>();
states.put(v, old_states);
} else {
for (State old_sv : old_states) {
if (eDominates(old_sv, new_sv)) {
continue STATE;
}
}
Iterator<State> iter = old_states.iterator();
while (iter.hasNext()) {
State old_sv = iter.next();
if (eDominates(new_sv, old_sv)) {
iter.remove();
}
}
}
if (traverseVisitor != null) traverseVisitor.visitEnqueue(new_sv);
old_states.add(new_sv);
pq.insert(new_sv, new_sv.getWeight() + h);
}
}
}
}
storeMemory();
// Make the states into paths and return them
List<GraphPath> paths = new LinkedList<GraphPath>();
for (State s : returnStates) {
LOG.debug(s.toStringVerbose());
paths.add(new GraphPath(s, true));
}
// sort by arrival time, though paths are already in order of increasing difficulty
// Collections.sort(paths, new PathComparator(origin.getOptions().isArriveBy()));
return paths;
}